Examples with MatrixMeta com.tencent.angel.ml.matrix.MatrixMeta used on opensource projects

Example 41 with MatrixMeta

use of com.tencent.angel.ml.matrix.MatrixMeta in project angel by Tencent.

the class RowSplitCombineUtils method combineIndexRowSplits.

/**
 * Combine the row splits.
 *
 * @param matrixId Matrix id
 * @param rowId row id
 * @param resultSize keys number
 * @param keyParts keys partitions
 * @param valueParts values partitions
 * @return merged vector
 */
public static Vector combineIndexRowSplits(int matrixId, int rowId, int resultSize, KeyPart[] keyParts, ValuePart[] valueParts) {
    // Get matrix meta
    MatrixMeta matrixMeta = PSAgentContext.get().getMatrixMetaManager().getMatrixMeta(matrixId);
    RowType rowType = matrixMeta.getRowType();
    switch(rowType) {
        case T_DOUBLE_DENSE:
        case T_DOUBLE_SPARSE:
            return combineIntDoubleIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_FLOAT_DENSE:
        case T_FLOAT_SPARSE:
            return combineIntFloatIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_INT_DENSE:
        case T_INT_SPARSE:
            return combineIntIntIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_LONG_DENSE:
        case T_LONG_SPARSE:
            return combineIntLongIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_DOUBLE_SPARSE_LONGKEY:
            return combineLongDoubleIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_FLOAT_SPARSE_LONGKEY:
            return combineLongFloatIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_INT_SPARSE_LONGKEY:
            return combineLongIntIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_LONG_SPARSE_LONGKEY:
            return combineLongLongIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        default:
            throw new UnsupportedOperationException("unsupport row type " + rowType);
    }
}

Example 42 with MatrixMeta

use of com.tencent.angel.ml.matrix.MatrixMeta in project angel by Tencent.

the class UserRequestAdapter method update.

public Future<VoidResult> update(int matrixId, int[] rowIds, Vector[] rows, UpdateOp op) {
    assert rowIds.length == rows.length;
    checkParams(matrixId, rowIds);
    for (int i = 0; i < rowIds.length; i++) {
        rows[i].setRowId(rowIds[i]);
    }
    MatrixMeta matrixMeta = PSAgentContext.get().getMatrixMetaManager().getMatrixMeta(matrixId);
    PartitionKey[] parts = matrixMeta.getPartitionKeys();
    CompStreamKeyValuePart[] splits = RouterUtils.splitStream(matrixMeta, rows);
    int needRequestPartNum = noEmptyPartNum(splits);
    FutureResult<VoidResult> result = new FutureResult<>();
    if (needRequestPartNum == 0) {
        result.set(null);
        return result;
    }
    UpdateRowsRequest request = new UpdateRowsRequest(matrixId, op);
    ResponseCache cache = new MapResponseCache(needRequestPartNum);
    int requestId = request.getRequestId();
    requestIdToResponseCache.put(requestId, cache);
    requestIdToResultMap.put(requestId, result);
    requests.put(requestId, request);
    MatrixTransportClient matrixClient = PSAgentContext.get().getMatrixTransportClient();
    for (int i = 0; i < splits.length; i++) {
        if (splits[i] != null && splits[i].size() > 0) {
            sendUpdateRequest(matrixClient, requestId, matrixId, parts[i].getPartitionId(), splits[i], op);
        }
    }
    return result;
}

Example 43 with MatrixMeta

use of com.tencent.angel.ml.matrix.MatrixMeta in project angel by Tencent.

the class UserRequestAdapter method update.

public Future<VoidResult> update(int matrixId, Matrix delta, UpdateOp op) {
    checkParams(matrixId);
    delta.setMatrixId(matrixId);
    MatrixMeta matrixMeta = PSAgentContext.get().getMatrixMetaManager().getMatrixMeta(matrixId);
    PartitionKey[] parts = matrixMeta.getPartitionKeys();
    CompStreamKeyValuePart[] splits = RouterUtils.splitStream(matrixMeta, delta);
    int needRequestPartNum = noEmptyPartNum(splits);
    FutureResult<VoidResult> result = new FutureResult<>();
    if (needRequestPartNum == 0) {
        result.set(null);
        return result;
    }
    UpdateMatrixRequest request = new UpdateMatrixRequest(matrixId, op);
    ResponseCache cache = new MapResponseCache(needRequestPartNum);
    int requestId = request.getRequestId();
    requestIdToResponseCache.put(requestId, cache);
    requestIdToResultMap.put(requestId, result);
    requests.put(requestId, request);
    MatrixTransportClient matrixClient = PSAgentContext.get().getMatrixTransportClient();
    for (int i = 0; i < splits.length; i++) {
        if (splits[i] != null && splits[i].size() > 0) {
            sendUpdateRequest(matrixClient, requestId, matrixId, parts[i].getPartitionId(), splits[i], op);
        }
    }
    return result;
}

Example 44 with MatrixMeta

use of com.tencent.angel.ml.matrix.MatrixMeta in project angel by Tencent.

the class UserRequestAdapter method get.

private FutureResult<Vector> get(IndexGetRowRequest request) {
    MatrixMeta matrixMeta = PSAgentContext.get().getMatrixMetaManager().getMatrixMeta(request.getMatrixId());
    PartitionKey[] parts = matrixMeta.getPartitionKeys();
    // Split the user request to partition requests
    FutureResult<Vector> result = new FutureResult<>();
    KeyPart[] splits;
    long startTs = System.currentTimeMillis();
    if (request instanceof IntIndexGetRowRequest) {
        splits = RouterUtils.split(matrixMeta, -1, ((IntIndexGetRowRequest) request).getKeys());
    } else if (request instanceof LongIndexGetRowRequest) {
        splits = RouterUtils.split(matrixMeta, -1, ((LongIndexGetRowRequest) request).getKeys());
    } else {
        throw new UnsupportedOperationException("Unsupport index request type " + request.getClass().toString());
    }
    LOG.info("Get by indices split use time: " + (System.currentTimeMillis() - startTs));
    assert parts.length == splits.length;
    // filter empty partition requests
    int needRequestPartNum = noEmptyPartNum(splits);
    if (needRequestPartNum == 0) {
        result.set(null);
        return result;
    }
    // Create partition results cache
    ResponseCache cache = new MapResponseCache(needRequestPartNum);
    int requestId = request.getRequestId();
    requestIdToResponseCache.put(requestId, cache);
    requestIdToResultMap.put(requestId, result);
    requests.put(requestId, request);
    // Send all the partition requests
    MatrixTransportClient matrixClient = PSAgentContext.get().getMatrixTransportClient();
    for (int i = 0; i < splits.length; i++) {
        if (splits[i] != null && splits[i].size() > 0) {
            sendIndexGetRowRequest(matrixClient, requestId, request.getMatrixId(), request.getRowId(), parts[i].getPartitionId(), splits[i], request.getFunc());
        }
    }
    return result;
}

Example 45 with MatrixMeta

use of com.tencent.angel.ml.matrix.MatrixMeta in project angel by Tencent.

the class MergeUtils method combineIndexRowSplits.

/**
 * Combine the row splits.
 *
 * @param matrixId Matrix id
 * @param rowId row id
 * @param resultSize keys number
 * @param keyParts keys partitions
 * @param valueParts values partitions
 * @return merged vector
 */
public static Vector combineIndexRowSplits(int matrixId, int rowId, int resultSize, KeyPart[] keyParts, ValuePart[] valueParts) {
    // Get matrix meta
    MatrixMeta matrixMeta = PSAgentContext.get().getMatrixMetaManager().getMatrixMeta(matrixId);
    RowType rowType = matrixMeta.getRowType();
    switch(rowType) {
        case T_DOUBLE_DENSE:
        case T_DOUBLE_SPARSE:
            return combineIntDoubleIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_FLOAT_DENSE:
        case T_FLOAT_SPARSE:
            return combineIntFloatIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_INT_DENSE:
        case T_INT_SPARSE:
            return combineIntIntIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_LONG_DENSE:
        case T_LONG_SPARSE:
            return combineIntLongIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_DOUBLE_SPARSE_LONGKEY:
            return combineLongDoubleIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_FLOAT_SPARSE_LONGKEY:
            return combineLongFloatIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_INT_SPARSE_LONGKEY:
            return combineLongIntIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        case T_LONG_SPARSE_LONGKEY:
            return combineLongLongIndexRowSplits(matrixId, rowId, resultSize, keyParts, valueParts, matrixMeta);
        default:
            throw new UnsupportedOperationException("unsupport row type " + rowType);
    }
}